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Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
Number of nodes: 9107
Number of edges: 410519
Running Louvain algorithm...
Maximum modularity in 10 random starts: 0.9383
Number of communities: 7
Elapsed time: 0 seconds
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
Number of nodes: 9107
Number of edges: 410519
Running Louvain algorithm...
Maximum modularity in 10 random starts: 0.9007
Number of communities: 9
Elapsed time: 0 seconds
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
Number of nodes: 9107
Number of edges: 410519
Running Louvain algorithm...
Maximum modularity in 10 random starts: 0.8746
Number of communities: 14
Elapsed time: 0 seconds
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
Number of nodes: 9107
Number of edges: 410519
Running Louvain algorithm...
Maximum modularity in 10 random starts: 0.8516
Number of communities: 14
Elapsed time: 0 seconds
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
Number of nodes: 9107
Number of edges: 410519
Running Louvain algorithm...
Maximum modularity in 10 random starts: 0.8312
Number of communities: 16
Elapsed time: 0 seconds
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
Number of nodes: 9107
Number of edges: 410519
Running Louvain algorithm...
Maximum modularity in 10 random starts: 0.8164
Number of communities: 19
Elapsed time: 0 seconds
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
Number of nodes: 9107
Number of edges: 410519
Running Louvain algorithm...
Maximum modularity in 10 random starts: 0.8028
Number of communities: 20
Elapsed time: 0 seconds
Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
Number of nodes: 9107
Number of edges: 410519
Running Louvain algorithm...
Maximum modularity in 10 random starts: 0.7900
Number of communities: 21
Elapsed time: 0 seconds
UMAP Clustering after batch correction at different resolutions

Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
Number of nodes: 9107
Number of edges: 410519
Running Louvain algorithm...
Maximum modularity in 10 random starts: 0.8746
Number of communities: 14
Elapsed time: 0 seconds
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>
<simpleWarning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session>





0mM 5mM
0mM 1.0000000 0.6908695
5mM 0.6908695 1.0000000

Feature plots UMAP
Feature plots PCA

Error in .subscript.2ary(x, i, , drop = TRUE) : subscript out of bounds
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Error in .subscript.2ary(x, i, , drop = TRUE) : subscript out of bounds
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Error in .subscript.2ary(x, i, , drop = TRUE) : subscript out of bounds
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[1] "result" "meta"



R version 4.3.1 (2023-06-16)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 22.04.2 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so; LAPACK version 3.10.0
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
time zone: Etc/UTC
tzcode source: system (glibc)
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] openxlsx_4.2.5.2 DESeq2_1.40.2
[3] pheatmap_1.0.12 compareGroups_4.8.0
[5] kableExtra_1.4.0 clustree_0.5.1
[7] ggraph_2.2.1 CATALYST_1.24.0
[9] reshape2_1.4.4 pals_1.8
[11] gprofiler2_0.2.3 viridis_0.6.5
[13] viridisLite_0.4.2 cowplot_1.1.3
[15] randomcoloR_1.1.0.1 RCurl_1.98-1.14
[17] RColorBrewer_1.1-3 data.table_1.15.4
[19] lubridate_1.9.3 forcats_1.0.0
[21] stringr_1.5.1 dplyr_1.1.4
[23] purrr_1.0.2 readr_2.1.5
[25] tidyr_1.3.1 tibble_3.2.1
[27] tidyverse_2.0.0 scater_1.28.0
[29] scuttle_1.10.3 Seurat_5.0.3
[31] SeuratObject_5.0.1 sp_2.1-3
[33] SingleCellExperiment_1.24.0 ggpubr_0.6.0
[35] ggplot2_3.5.0 SingleR_2.2.0
[37] SummarizedExperiment_1.32.0 Biobase_2.62.0
[39] GenomicRanges_1.54.1 GenomeInfoDb_1.38.1
[41] IRanges_2.36.0 S4Vectors_0.40.2
[43] BiocGenerics_0.48.1 MatrixGenerics_1.14.0
[45] matrixStats_1.3.0 workflowr_1.7.1
loaded via a namespace (and not attached):
[1] dichromat_2.0-0.1 nnet_7.3-19
[3] goftest_1.2-3 DT_0.33
[5] TH.data_1.1-2 vctrs_0.6.5
[7] spatstat.random_3.2-3 digest_0.6.35
[9] png_0.1-8 shape_1.4.6.1
[11] git2r_0.33.0 ggrepel_0.9.5
[13] httpcode_0.3.0 deldir_2.0-4
[15] parallelly_1.37.1 fontLiberation_0.1.0
[17] MASS_7.3-60.0.1 httpuv_1.6.15
[19] foreach_1.5.2 withr_3.0.0
[21] ggrastr_1.0.2 xfun_0.43
[23] survival_3.5-8 crul_1.4.2
[25] memoise_2.0.1 ggbeeswarm_0.7.2
[27] RProtoBufLib_2.12.1 drc_3.0-1
[29] systemfonts_1.0.6 ragg_1.3.0
[31] zoo_1.8-12 GlobalOptions_0.1.2
[33] gtools_3.9.5 V8_4.4.2
[35] pbapply_1.7-2 promises_1.3.0
[37] httr_1.4.7 rstatix_0.7.2
[39] globals_0.16.3 fitdistrplus_1.1-11
[41] ps_1.7.6 rstudioapi_0.16.0
[43] pan_1.9 miniUI_0.1.1.1
[45] generics_0.1.3 processx_3.8.4
[47] curl_5.2.1 zlibbioc_1.48.0
[49] ScaledMatrix_1.8.1 polyclip_1.10-6
[51] GenomeInfoDbData_1.2.11 SparseArray_1.2.2
[53] xtable_1.8-4 doParallel_1.0.17
[55] evaluate_0.23 S4Arrays_1.2.0
[57] glmnet_4.1-8 hms_1.1.3
[59] irlba_2.3.5.1 colorspace_2.1-0
[61] ROCR_1.0-11 reticulate_1.36.0
[63] spatstat.data_3.0-4 magrittr_2.0.3
[65] lmtest_0.9-40 later_1.3.2
[67] lattice_0.22-6 mapproj_1.2.11
[69] spatstat.geom_3.2-9 future.apply_1.11.2
[71] getPass_0.2-4 scattermore_1.2
[73] XML_3.99-0.16.1 RcppAnnoy_0.0.22
[75] pillar_1.9.0 nlme_3.1-164
[77] iterators_1.0.14 compiler_4.3.1
[79] beachmat_2.16.0 RSpectra_0.16-1
[81] stringi_1.8.3 jomo_2.7-6
[83] minqa_1.2.6 tensor_1.5
[85] plyr_1.8.9 crayon_1.5.2
[87] abind_1.4-5 truncnorm_1.0-9
[89] chron_2.3-61 locfit_1.5-9.9
[91] graphlayouts_1.1.1 sandwich_3.1-0
[93] whisker_0.4.1 codetools_0.2-20
[95] multcomp_1.4-25 textshaping_0.3.7
[97] BiocSingular_1.16.0 openssl_2.1.1
[99] flextable_0.9.5 crosstalk_1.2.1
[101] bslib_0.7.0 GetoptLong_1.0.5
[103] plotly_4.10.4 mime_0.12
[105] splines_4.3.1 circlize_0.4.16
[107] Rcpp_1.0.12 fastDummies_1.7.3
[109] sparseMatrixStats_1.12.2 knitr_1.46
[111] utf8_1.2.4 clue_0.3-65
[113] lme4_1.1-35.2 fs_1.6.3
[115] listenv_0.9.1 checkmate_2.3.1
[117] nnls_1.5 DelayedMatrixStats_1.22.6
[119] ggsignif_0.6.4 Matrix_1.6-5
[121] callr_3.7.6 tzdb_0.4.0
[123] svglite_2.1.3 tweenr_2.0.3
[125] pkgconfig_2.0.3 tools_4.3.1
[127] cachem_1.0.8 fastmap_1.1.1
[129] rmarkdown_2.26 scales_1.3.0
[131] grid_4.3.1 ica_1.0-3
[133] officer_0.6.5 broom_1.0.5
[135] sass_0.4.9 patchwork_1.2.0
[137] dotCall64_1.1-1 carData_3.0-5
[139] rpart_4.1.23 RANN_2.6.1
[141] farver_2.1.1 tidygraph_1.3.1
[143] yaml_2.3.8 cli_3.6.2
[145] writexl_1.5.0 leiden_0.4.3.1
[147] lifecycle_1.0.4 askpass_1.2.0
[149] uwot_0.2.1 mvtnorm_1.2-4
[151] backports_1.4.1 BiocParallel_1.34.2
[153] cytolib_2.12.1 timechange_0.3.0
[155] gtable_0.3.4 rjson_0.2.21
[157] ggridges_0.5.6 progressr_0.14.0
[159] parallel_4.3.1 limma_3.56.2
[161] jsonlite_1.8.8 mitml_0.4-5
[163] RcppHNSW_0.6.0 bitops_1.0-7
[165] openxlsx2_1.5 Rtsne_0.17
[167] FlowSOM_2.8.0 spatstat.utils_3.0-4
[169] BiocNeighbors_1.18.0 zip_2.3.1
[171] flowCore_2.12.2 mice_3.16.0
[173] jquerylib_0.1.4 highr_0.10
[175] lazyeval_0.2.2 shiny_1.8.1.1
[177] ConsensusClusterPlus_1.64.0 htmltools_0.5.8.1
[179] sctransform_0.4.1 gfonts_0.2.0
[181] glue_1.7.0 spam_2.10-0
[183] XVector_0.42.0 gdtools_0.3.7
[185] rprojroot_2.0.4 Rsolnp_1.16
[187] gridExtra_2.3 boot_1.3-30
[189] igraph_2.0.3 R6_2.5.1
[191] labeling_0.4.3 cluster_2.1.6
[193] nloptr_2.0.3 DelayedArray_0.28.0
[195] tidyselect_1.2.1 vipor_0.4.7
[197] plotrix_3.8-4 maps_3.4.2
[199] xml2_1.3.6 ggforce_0.4.2
[201] fontBitstreamVera_0.1.1 car_3.1-2
[203] future_1.33.2 rsvd_1.0.5
[205] munsell_0.5.1 KernSmooth_2.23-22
[207] fontquiver_0.2.1 htmlwidgets_1.6.4
[209] ComplexHeatmap_2.16.0 rlang_1.1.3
[211] spatstat.sparse_3.0-3 spatstat.explore_3.2-7
[213] uuid_1.2-0 colorRamps_2.3.4
[215] HardyWeinberg_1.7.8 ggnewscale_0.4.10
[217] fansi_1.0.6 beeswarm_0.4.0